Quantum sensing (QS) exploits non-classical physical phenomena for advanced measurement, with growing relevance to infrastructure monitoring. Despite laboratory-level progress, real-world deployment remains uneven, shaped by integration complexity, digital connectivity, and technological maturity. This article presents a systematic review of QS technologies focused on deployability within infrastructure monitoring architectures. Following PRISMA 2020 guidelines, searches were conducted across six bibliographic databases, covering the 2017–2025 period. An initial dataset of 3,636 records was retrieved and reduced through a multi-stage screening pipeline which progressively narrowed the corpus to a final set of 80 peer-reviewed publications retained for detailed analysis. Studies were classified by QS modality, readout architecture, physical platform, and application domain encompassing geophysical and subsurface monitoring, civil and structural health monitoring, transport systems, and urban and environmental sensing. A cross-modality performance comparison was conducted using reported quantitative metrics including sensitivity, resolution, and bandwidth to benchmark quantum sensor technologies against classical sensing baselines, contextualizing their deployment feasibility. Readiness for real-world deployment was assessed using an adapted quantum technology readiness level framework, emphasizing system-level integration, operational sustainability, and compatibility with internet of things enabled and digitally connected monitoring infrastructures. Results reveal heterogeneous maturity trajectories across quantum sensor subtypes and highlight the critical roles of hybrid quantum–classical architectures, edge processing, and secure data integration for scalable deployment. This review positions QS as an enabling component within digitally integrated monitoring systems and provides a realistic perspective on the conditions under which quantum sensor technologies can contribute effectively to future infrastructure monitoring applications.
Quantum sensing (QS) exploits non-classical physical phenomena for advanced measurement, with growing relevance to infrastructure monitoring. Despite laboratory-level progress, real-world deployment remains uneven, shaped by integration complexity, digital connectivity, and technological maturity. This article presents a systematic review of QS technologies focused on deployability within infrastructure monitoring architectures. Following PRISMA 2020 guidelines, searches were conducted across six bibliographic databases, covering the 2017–2025 period. An initial dataset of 3,636 records was retrieved and reduced through a multi-stage screening pipeline which progressively narrowed the corpus to a final set of 80 peer-reviewed publications retained for detailed analysis. Studies were classified by QS modality, readout architecture, physical platform, and application domain encompassing geophysical and subsurface monitoring, civil and structural health monitoring, transport systems, and urban and environmental sensing. A cross-modality performance comparison was conducted using reported quantitative metrics including sensitivity, resolution, and bandwidth to benchmark quantum sensor technologies against classical sensing baselines, contextualizing their deployment feasibility. Readiness for real-world deployment was assessed using an adapted quantum technology readiness level framework, emphasizing system-level integration, operational sustainability, and compatibility with internet of things enabled and digitally connected monitoring infrastructures. Results reveal heterogeneous maturity trajectories across quantum sensor subtypes and highlight the critical roles of hybrid quantum–classical architectures, edge processing, and secure data integration for scalable deployment. This review positions QS as an enabling component within digitally integrated monitoring systems and provides a realistic perspective on the conditions under which quantum sensor technologies can contribute effectively to future infrastructure monitoring applications.
Quantum technology is revolutionizing the next generation of intelligent and secure sensing systems.This review explores how quantum sensors—leveraging principles of superposition, entanglement, and quantum tunneling—can be integrated with Internet of Things (IoT) and cloud computing infrastructures to achieve ultra-high precision, real-time analytics, and quantum-secure communication.It discusses the fundamental mechanisms of quantum sensing, sensor architectures, and hybrid quantum-classical data models.The paper also reviews Quantum-Enabled IoT (QIoT) frameworks, Quantum Cloud Computing (QCC) platforms such as IBM Quantum and AWS Braket, and highlights challenges including decoherence, scalability, and standardization.Finally, it presents the future direction of Quantum Industry 5.0, emphasizing sustainable, secure, and intelligent cyber-physical systems powered by quantum innovation.
The vital role of civil engineering is to enable the development of modern cities and establish foundations for smart and sustainable urban environments of the future. Advanced sensing technologies are among the instrumental methods used to enhance the performance of civil engineering infrastructures and address the multifaceted challenges of future cities. Through this study, we discussed the shortcomings of traditional sensors in four primary civil engineering domains: construction, energy, water, and transportation. Then, we investigated and summarized the potential of quantum sensors to contribute to and revolutionize the management of civil engineering infrastructures. For the water sector, advancements are expected in monitoring water quality and pressure in water and sewage infrastructures. In the energy sector, quantum sensors may facilitate renewables integration and improve grid stability and buildings’ energy efficiency. The most promising progress in the construction field is the ability to identify subsurface density and underground structures. In transportation, these sensors create many fresh avenues for real-time traffic management and smart mobility solutions. As one of the first-in-the-field studies offering the adoption of quantum sensors across four primary domains of civil engineering, this research establishes the basis for the discourse about the scope and timeline for deploying quantum sensors to real-world applications towards the quantum transformation of civil engineering.
This chapter explores the transformative integration of Quantum Computing (QC) with the Internet of Things (IoT), highlighting significant advancements in security, optimization, and intelligent decision-making for cyber-physical systems. It provides a detailed review of quantum-enhanced algorithms, architectures, and sensing technologies designed for IoT ecosystems. Addressing the limitations of traditional methods in large-scale computation, network optimization, data analytics, and security, the chapter emphasizes core quantum concepts, i.e., superposition, entanglement, and interference. Techniques, including quantum annealing and the QAOA, enable efficient resource allocation, scheduling, and routing in emerging infrastructures like 6G and UAV networks. The use of hybrid quantum–classical models is examined for fault detection, cryptographic key generation, and real-time analytics across edge-to-cloud environments. QML has been shown to enhance adaptive learning and pattern recognition on resource-limited devices. To counter emerging cyber threats, quantum-resilient security solutions, including post-quantum cryptography, quantum random number generation, and quantum key distribution, are discussed. The chapter also highlights quantum sensors that utilize tunnelling, spin dynamics, and interference for applications in biomedical diagnostics, environmental monitoring, infrastructure evaluation, and autonomous navigation. Emerging use cases, including quantum-powered digital marketing and quantum-secured smart locks, are introduced. The chapter concludes by underscoring the transformative role of scalable hybrid QC–IoT architectures, which are poised to advance edge intelligence, smart infrastructure, healthcare, and logistics, while opening new directions for research and real-world deployment.
Cyber-physical systems (CPSs) based on the Internet of Things (IoT) form the backbone of modern smart infrastructures, including smart cities, healthcare monitoring, industrial automation, and intelligent transportation. However, connecting many resource-limited IoT devices makes them more vulnerable to cyber threats, particularly quantum attacks. This review comprehensively examines quantum-secure communication (QSC) frameworks for IoT-enabled CPS, focusing on Quantum Key Distribution (QKD), post-quantum cryptographic (PQC) algorithms, and hybrid quantum–classical security models suitable for constrained devices. A PRISMA-guided search of the Scopus and Google Scholar database was conducted in January 2026 using three keyword groups related to hybrid security, artificial intelligence, and cyber-physical systems. Based on the evaluation, 6008 publications have been identified between 2001 and 2026. The first-round screening was performed for 4948 articles, after excluding duplicates. During the screening stage, 348 articles were selected for abstract scrutiny, 115 records were excluded due to no direct focus on CPS/IoT applications, 52 studies were excluded because these papers relied on traditional security models, 25 studies were excluded due to insufficient relevance to the review objectives, and 15 additional non-English studies were removed. Following the screening stage, 141 studies were selected for full-text eligibility. Out of those, 86 studies were removed due to a lack of specific evaluation metrics or not being published in a peer-reviewed venue. Furthermore, the publications are classified as QKD-based secure CPS and QSC for industrial IoT, AI-Assisted Secure Communication for CPS Networks, and hybrid PQC-QKD models for CPS/IoT devices. This article investigates recent advancements in secure data transmission, verified protocols, and AI-driven anomaly detection customized to CPS/IoT environments. In addition, operational hurdles, interaction with open innovations, real-time deployment, and secure edge-cloud integration are highlighted. By analyzing recent developments and identifying research gaps, this review provides a structured roadmap for designing secure, scalable, and quantum-safe IoT-based CPS frameworks capable of withstanding next-generation cyber threats. This systematic review was performed and reported according to the PRISMA 2020 guidelines.
Quantum technologies are moving from foundational science toward engineered systems in sensing and metrology, computing and simulation, communication and networking, and security. The transition is uneven in technological maturity: atomic clocks and several quantum sensors are operational; quantum key distribution has reached field deployment but remains constrained by integration, assurance and network architecture; post-quantum cryptography is entering standards-based migration; and general-purpose fault-tolerant quantum computing remains an engineering objective despite major progress in error correction. This treatise develops a mathematically grounded and application-oriented account of what quantum technologies are, what physical resources they exploit, what advantages have been proved or demonstrated, and where claims remain speculative. It distinguishes among scientific feasibility, engineering readiness, operational utility, economic value and societal legitimacy. Across fundamental physics, Earth and space sciences, environmental monitoring, health and life sciences, cybersecurity, critical infrastructure, hazards, defense, finance, decision support and AI-enabled systems, this work identifies bottlenecks and proposes a systems roadmap for robust, scalable, efficient, verifiable and responsible quantum-enabled capabilities.
Abstract. Quantum sensing technologies provide future cities with unimaginable techniques for solving their complex problems. Quantum sensors, through the utilization of quantum effects such as superposition, entanglement, and tunneling, can provide an unmatched level of sensitivity, precision, and durability against traditional sensing technologies. This study explores the potential applications of quantum sensing in four critical urban infrastructure domains: water, energy, transport, and construction. Throughout this study, we determine the most promising quantum sensing technologies for each domain. Besides, we discuss the technical progress of these sensors and the advantages they have in comparison with classical devices, as well as the organizational issues cities can face when implementing these sensors. Our results indicate that quantum sensing will be a critical enabler of future smart cities, generating advanced monitoring, control, and decision-making capabilities across various sectors. Nevertheless, taking advantage of this potential will demand the close partnership of cities, industry, academia, and policymakers to guide the complicated adoption process.